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Engineering, Mathematics, Statistics, Computer Science or conjugate subject; strong record of publication in the relevant literature; good knowledge of machine learning algorithms and/or statistical methods
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• Uncertainty quantification around LLMs • Constrained optimal experimental design (active learning) • Combining models and combining data / Realistic simulation of clinical trials • Developing
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scientists, and researchers working on medical image analysis, machine learning, and audiology. Our recent work has focused on using deep learning to analyse temporal bone CT scans and brain MRI data in
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Science, Robotics, AI, or a related field Strong background in machine learning and robotics, with specialisation in one or more of the following areas: generative models, reinforcement learning, human-centred AI
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Science, Robotics, AI, or a related field 2. Strong background in machine learning and robotics, with specialisation in one or more of the following areas: generative models, reinforcement learning, human
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. Familiarity with standard design verification (DV) procedures and continuous integration (CI) setups would be beneficial. Knowledge of machine learning workloads and the design of machine-learning accelerators
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developing characterisations of network models and interactions with methods in statistical machine learning. The post holder provides guidance to junior members of the research group including project
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developing characterisations of network models and interactions with methods in statistical machine learning. The post holder provides guidance to junior members of the research group including project
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evaluations, attacks on and defensive mechanisms for safe multi-agent systems, powered by LLM and VLM models. Candidates should possess a PhD (or be near completion) in Machine Learning or a highly related
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skills, proficiency in quantitative analysis of large datasets and working with pre-trained machine learning models is desirable but not essential To apply online for this vacancy and to view further